Characteristics and determinants of personal exposure to PM2.5 mass and components in adult subjects in the megacity of Guangzhou, China

被引:13
作者
Chen, Xiao-Cui [1 ,9 ]
Jahn, Heiko J. [2 ]
Ward, Tony J. [3 ]
Ho, Hung Chak [4 ]
Luo, Ming [5 ,6 ]
Engling, Guenter [7 ,8 ]
Kraemer, Alexander [2 ]
机构
[1] Chinese Univ Hong Kong, Inst Environm Energy & Sustainabil, Hong Kong, Peoples R China
[2] Bielefeld Univ, Sch Publ Hlth, Bielefeld, Germany
[3] Univ Montana, Sch Publ & Community Hlth Sci, Missoula, MT 59812 USA
[4] Univ Hong Kong, Dept Urban Planning & Design, Hong Kong, Peoples R China
[5] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou, Peoples R China
[6] Sun Yat Sen Univ, Guangdong Key Lab Urbanizat & Geosimulat, Guangzhou, Peoples R China
[7] Desert Res Inst, Div Atmospher Sci, Reno, NV USA
[8] Calif Air Resources Board, El Monte, CA USA
[9] Chinese Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Personal exposure; PM2.5; constituents; Within-subject variability; Mixed-effects model; FINE PARTICULATE MATTER; AMBIENT-GENERATED EXPOSURE; PEARL RIVER DELTA; AIR-POLLUTION; PARTICLES PM2.5; CHEMICAL-COMPOSITIONS; BIOMASS COMBUSTION; ELEMENTAL CARBON; ORGANIC-MATTER; HAZE EVENTS;
D O I
10.1016/j.atmosenv.2020.117295
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding the heterogeneity between ambient concentration and personal exposure is crucial in studies regarding the health risks of air pollution exposure. We performed a panel study with 4-19 (average = 10) repeated personal monitoring in 16 adult subjects (ages 18-30) for three consecutive weeks during the winter and summer of 2011-2012 in the Chinese megacity of Guangzhou. Also, we conducted simultaneous ambient measurements at eight districts (including five urban sites, two suburban locations, and one rural site) of Guangzhou. Significant seasonal variations were shown in personal PM2.5 exposure for most of the analyzed components (p < 0.05), with higher levels in winter than in summer. Average personal exposures exhibited a pattern of central urban > suburban > rural areas for PM2.5 mass and most of the constituents (e.g., carbonaceous aerosols, ions). We applied mixed-effects models to estimate within- and between-subject variance components and determinants of personal PM2.5 exposure after adjusting for potential confounders. The within-subject variance component dominated the total variability (63.7-95.6%) for most of the investigated PM2.5 components. Ambient PM2.5 mass and its components were the dominant predictors and contributors of the corresponding personal exposures (0.11 < R-c(2) < 0.97; p < 0.05). The results indicate that season and district type affect personal PM2.5 exposure and its components, contributing to 4.9-51.6% and 8.0-77.8% of the variability. Time indoors and outdoors were also factors affecting personal exposure. The study findings revealed ambient concentrations at a fixed monitoring station underestimated residents' true exposure levels. In conclusion, the current study emphasizes the need for incorporating spatio-temporal activity patterns complementing evenlydistributed air quality monitoring networks to increase the estimation power in epidemiological analysis linking true personal exposure to health effects.
引用
收藏
页数:14
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